Talking to journalists about AIs

Communicating correctly and timely about AI is too important to be neglected by AI researchers. This tutorial gives you the basic understanding of what does it take to talk to journalists about your work and AI in general


This tutorial is not what typically one would find among ECAI tutorials, but we believe that it is timely and extremely indirectly important to AI research in general. The specialised nature of AI concepts and processes is often lost on journalists. Effective communication of one’s research is critical to ensure a clear understanding of the message, as AI technology may significantly impact society. Consequently, the need for simplification and populari- sation aligns with the communication standards of journalism. Researchers are not necessarily good communicators. However, properly disseminating AI-related information to journalists serves not only as a bridge between science and news media dissemination but also as a means of fostering a broader societal understanding of the implications and advances of AI research.

Last year (2023) we saw a culmination of public interest in AI. This was prima facie motivated by ChatGPT and other generative technology, but in actuality because generative AI applications allowed people with no understanding of computation and AI to use computation and AI. Increased nvestment in AI startups 1 has further motivated the interest in AI from non-professionals. As a result a lot of journalists were interested in reaching out to people with AI expertise to answer different questions on AI. Excellent AI researchers are not necessarily excellent communicators. Excellent communicators do not necessarily understand AI. The misunderstanding of AI by the general public is very likely to bring a negative backlash on AI research by impacting our funding, while allowing for various fraudulent products to be developed and tested in society. It is there in the mutual interest of both society and AI research for AI experts to learn how to communicate about their work and AI basics to journalists who can then bring actual expertise into the world.

This tutorial is aimed at experienced researchers but it is also accessible to young students because it does not ask for any knowledge prerequisites. We consider that this type of training, that we offer in the tutorial should be integrated into AI doctoral training programs overall, in the broader perspective of developing the communication skills needed to make research accessible outside academia.

The tutorial will cover the basic of what journalistic work and process. We will then explain some colloquialisms such as: audience, interviews, different journalistic forms (article, interview, opinion), what does it mean to “be clear”, what is a “sound bite”, what does it mean to explain something “in simple terms”, ensuring that researchers can effectively communicate their work to a broader audience with different levels of expertise.

The tutorial will follow a two-part approach. In the first hour, participants will receive a presentation on the basic concepts of effective communication and journalism, supported by illustrative examples and counterexamples. The focus will be on understanding audience dynamics, narrative construction and the principles of practical journalism. During the second hour, the tutorial will facilitate an interactive experience. Participants will engage in a scenario-based activity that simulates an interview to apply the concepts learned. This hands-on segment is designed to reinforce practical skills, allowing participants to actively practice and refine their communication techniques in a supportive learning environment. This combined approach ensures that participants gain comprehensive set.


Laurence Dierickx holds a master's degree in Information Science and her PhD focused on machine generated content in the context of journalism, bridging technology and journalism. Since then, she cultivates an interdisciplinary approach in her research, focusing on data-centric AI, ethical AI systems, and the user experience of AI technology. Publication list available at Google Scholar.


Marija Slavkovik is the head of the department of Information Science and Media Studies which includes research groups in rhetoric, audiences and journalism. The department offers the top-ranked bachelor program in journalism in Norway. Through her role in the department, Marija interacts regularly with journalists and understands the basic aspects of journalism and media research. For a full list of publications see here. The details of activities and full list of publications can be found here.


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